内容来源：https://www.geekwire.com/2026/microsoft-exec-charles-lamanna-on-how-ai-is-creating-an-expensive-new-request-from-job-candidates/

内容总结：

在人工智能浪潮席卷全球的背景下，企业福利正被赋予全新内涵。微软高管近日透露，顶尖人才在求职时已开始将AI资源配额视为关键入职条件，这标志着AI工具正从实验性技术迅速转变为职场核心生产力要素。

微软业务应用与平台执行副总裁查尔斯·拉曼纳在近日的西雅图行业会议上分享了一个典型案例：某位求职者明确要求团队必须获得充足的AI算力配额（以代币形式计量）作为入职前提。尽管未透露具体金额，但他指出"日均代币成本可能达到数百美元量级"。

拉曼纳算了一笔经济账：若一名年薪成本50万美元的工程师要求10万美元的AI代币预算，同时能提升三倍工作效率，这对企业和员工将是双赢局面。他将限制AI资源比作剥夺工程师的鼠标、邮箱等基础工具，强调AI辅助编程工具已成为新一代"数字办公基础设施"。

这种趋势正在多个知识工作领域蔓延。英伟达CEO黄仁勋近期预言AI代币将成为硅谷招聘新筹码，风险投资家托马斯·通古兹更在博客中指出，到2026年AI推理成本可能成为继薪资、奖金、股权后的第四大工程师薪酬支柱。

《纽约时报》近期报道揭示了科技公司内部的新现象：员工通过"代币消耗排行榜"展开竞争，形成被称为"代币最大化"的职场新生态。这进一步印证了AI资源正在重塑职场文化、人才竞争格局和企业投资逻辑。

中文翻译：

在人工智能蓬勃发展的当下，职场福利正被赋予全新内涵。周二于西雅图举行的GeekWire"变革先锋"活动上，微软执行副总裁查尔斯·拉曼纳分享了一个案例：某位求职者表示，只要团队能获得特定额度的AI代币——即驱动人工智能系统交互的"燃料"，他就愿意入职。

拉曼纳虽未透露具体金额，但指出"上限大约是每天100至数百美元的代币成本"。这则轶事折射出，获取AI模型正变得与薪资待遇同等重要，也揭示着人工智能正以惊人速度从实验阶段融入日常工作的核心环节。

拉曼纳算了一笔账：若一位"全负荷成本"（企业为雇员承担的总支出）达50万美元的工程师，要求配备价值10万美元的代币资源，并因此将工作效率提升三倍，这对所有相关方而言都是笔超值交易。他将限制工程师AI资源的行为比作剥夺基础办公工具："设想上班时没有鼠标、没有邮箱、没有Teams软件——这就是习惯使用AI编程助手的工程师在代币预算紧缩时的真实感受。"

"招聘的内涵、全负荷成本的计算、企业的投资方向都将因此发生根本性变革。"这位微软商业应用与智能体部门负责人表示。他预见这种转变将超越软件工程领域，延伸至财务规划等多种办公室信息处理工作。"未来求职者可能会说：除非获得足够的代币预算，否则我不会接受这份工作。"

持此观点者并非只有拉曼纳。据美国消费者新闻与商业频道报道，英伟达首席执行官黄仁勋上周预言AI代币将成为"硅谷招聘新筹码"。风险投资家托马斯·通古兹上月则在博客中指出，推理成本可能成为继薪资、奖金、股权之后的工程师薪酬"第四支柱"。他写道："未来会以代币形式支付薪酬吗？到2026年，这种模式或许就将开启。"

《纽约时报》上周披露，科技公司员工正围绕追踪代币消耗的内部排行榜展开竞争，催生出名为"代币最大化"的新型职场地位博弈。

英文来源：

Work perks are taking on new meaning in the AI boom.
Speaking at GeekWire’s Agents of Transformation event in Seattle on Tuesday, Microsoft EVP Charles Lamanna talked about a job candidate who said they would come aboard as long as their team was given a certain dollar amount of AI tokens — the fuel that powers interactions with AI systems.
Lamanna didn’t reveal the exact dollar amount request, but said “you should think of $100 to hundreds of dollars of token cost per day, at the limit.”
The anecdote reflects how access to AI models is becoming as fundamental as salary — and how quickly AI is moving from experimentation to a core part of day-to-day work.
If a “fully loaded” (total cost of an employee to a company) engineer costs $500,000 a year and the employee asks for $100,000 worth of tokens — which makes them three times as efficient — Lamanna said it’s a great deal for everyone involved.
He compared denying engineers sufficient AI resources to stripping away basic workplace tools. Imagine showing up to work with no mouse, no email, no Microsoft Teams — that’s how an engineer accustomed to AI-powered coding agents would feel working under a tight token budget, he said.
“So how you think about what it means to hire, and fully loaded cost, and where we invest is going to change completely as a result of this,” said Lamanna, Microsoft’s executive vice president of Business Applications & Agents. He sees this happening beyond software engineering — to multiple other forms of office and information work, such as financial planning.
“They’ll be like, I’m not going to work there unless I actually get a certain amount of token budget,” he said.
Lamanna isn’t alone in seeing this shift. Nvidia CEO Jensen Huang last week said AI tokens would become “one of the recruiting tools in Silicon Valley,” CNBC reported. In a blog post last month, venture capitalist Tomasz Tunguz described inference costs as a potential fourth pillar of engineer compensation alongside salary, bonuses, and equity. “Will you be paid in tokens?” Tunguz wrote. “In 2026, you likely will start to be.”
The New York Times last week reported on how employees at tech companies are competing on internal leaderboards that track token consumption, creating a new status game called “tokenmaxxing.”